The present disclosure relates to systems and methods for magnetic resonance imaging (“MRI”). More particularly, systems and methods are described for optimizing acquisitions for magnetic resonance fingerprinting applications.
Magnetic resonance fingerprinting (“MRF”) is an imaging technique that enables quantitative mapping of tissue or other material properties based on random or pseudorandom measurements of the subject or object being imaged. Examples of parameters that can be mapped include longitudinal relaxation time, T1; transverse relaxation time, T2; main magnetic field map, B0; and proton density, ρ. MRF is generally described in, for example, U.S. Pat. No. 8,723,518, which is herein incorporated by reference in its entirety.
The random or pseudorandom measurements obtained in MRF techniques are achieved by varying the acquisition parameters from one repetition time (“TR”) period to the next, which creates a time series of images with varying contrast. Examples of acquisition parameters that can be varied include flip angle (“FA”), radio frequency (“RF”) pulse phase, TR, echo time (“TE”), and sampling patterns, such as by modifying one or more readout encoding gradients.
The data acquired with MRF techniques are compared with a dictionary of signal models, or templates, that have been generated for different acquisition parameters from magnetic resonance signal models, such as Bloch equation-based physics simulations. This comparison allows estimation of the desired physical parameters, such as those mentioned above. The parameters for the tissue or other material in a given voxel are estimated to be the values that provide the best signal template matching.
In order to reduce the scan time required for MRF, current methods either vastly undersample k-space by sampling along a single spiral at each acquisition or alternatively sample the entire k-space using an echo-planar imaging (“EPI”) based sampling. While each method has its advantages, they are not without drawbacks as well. For example, undersampling a spiral sampling trajectory yields significant artifacts, which then require a large number of acquisitions to obtain an accurate match. On the other hand, EPI-based methods suffer from field inhomogeneity artifacts inherent to EPI and are therefore not suitable for high fields.
Given the above, there remains a need for improved an MRF acquisition techniques.